Chip comparison
Groq LPU (Language Processing Unit) vs NVIDIA GB300 (Blackwell Ultra)
Side-by-side specs
Straight from each vendor's datasheet. Winner in bold: higher throughput, memory, or transistor count; lower power draw or price. Sparse (2:4) throughput roughly doubles the FP8/INT8 numbers shown.
| Field | Groq LPU (Language Processing Unit) | NVIDIA GB300 (Blackwell Ultra) |
|---|---|---|
| Process node | GlobalFoundries 14nm | TSMC 4NP |
| TDP | 375 W | 1400 W |
| Memory | 0.23 GB SRAM (230 MB on-die) | 288 GB HBM3e |
| Memory bandwidth | 80,000 GB/s | 8,000 GB/s |
| FP16 (dense) | 188 TFLOPS | — |
| FP8 (dense) | — | 5,000 TFLOPS |
| INT8 (dense) | 750 TOPS | — |
| Form factor | PCIe (GroqCard) / rack-scale GroqRack | Superchip (Blackwell Ultra + Grace) |
| Announced | 2020-01-01 | 2025-03-18 |
| Released | 2021-06-01 | 2025-11-01 |
Robots running Groq LPU (Language Processing Unit)
No robots publicly running it yet.
Robots running NVIDIA GB300 (Blackwell Ultra)
No robots publicly running it yet.
Data centers with Groq LPU (Language Processing Unit)
No data centers publicly running it yet.
Data centers with NVIDIA GB300 (Blackwell Ultra)
Common questions
Groq LPU (Language Processing Unit) vs NVIDIA GB300 (Blackwell Ultra): which is faster for training?
NVIDIA GB300 (Blackwell Ultra) has 26.60x the dense FP16/BF16 throughput of the other (Groq LPU (Language Processing Unit): 188 TFLOPS; NVIDIA GB300 (Blackwell Ultra): 5,000 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Groq LPU (Language Processing Unit) vs NVIDIA GB300 (Blackwell Ultra): which has more memory?
NVIDIA GB300 (Blackwell Ultra) carries more HBM (Groq LPU (Language Processing Unit): 0.23 GB SRAM (230 MB on-die); NVIDIA GB300 (Blackwell Ultra): 288 GB HBM3e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Groq LPU (Language Processing Unit) vs NVIDIA GB300 (Blackwell Ultra): which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Groq LPU (Language Processing Unit) 0.50 (188 ÷ 375 W); NVIDIA GB300 (Blackwell Ultra) 3.57 (5,000 ÷ 1400 W). NVIDIA GB300 (Blackwell Ultra) wins at the die level; system-level efficiency also depends on cooling and interconnect.
Groq LPU (Language Processing Unit) vs NVIDIA GB300 (Blackwell Ultra): which is more widely used?
Groq LPU (Language Processing Unit): 0 robots and 0 data centers publicly running it. NVIDIA GB300 (Blackwell Ultra): 0 robots and 1 data center. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · Groq LPU (Language Processing Unit) full page · NVIDIA GB300 (Blackwell Ultra) full page.